José A. Gámez, Serafin Moral, Antonio Salmerón Cerdan
In recent years probabilistic graphical models, especially Bayesian networks and decision graphs, have experienced significant theoretical development within areas such as artificial intelligence and statistics. This carefully edited monograph is a compendium of the most recent advances in the area of probabilistic graphical models such as decision graphs, learning from data and inference. It presents a survey of the state of the art of specific topics of recent interest of Bayesian Networks, including approximate propagation, abductive inferences, decision graphs, and applications of...
In recent years probabilistic graphical models, especially Bayesian networks and decision graphs, have experienced significant theoretical developm...
